Memory based on abstraction for dynamic fitness functions.

Date

2008

Advisors

Journal Title

Journal ISSN

ISSN

Volume Title

Publisher

Springer- Verlag.

Type

Article

Peer reviewed

Yes

Abstract

This paper proposes a memory scheme based on abstraction for evolutionary algorithms to address dynamic optimization problems. In this memory scheme, the memory does not store good solutions as themselves but as their abstraction, i.e., their approximate location in the search space. When the environment changes, the stored abstraction information is extracted to generate new individuals into the population. Experiments are carried out to validate the abstraction based memory scheme. The results show the efficiency of the abstraction based memory scheme for evolutionary algorithms in dynamic environments.

Description

Keywords

Citation

Richter, H. and Yang, S. (2008) Memory based on abstraction for dynamic fitness functions.In: Applications of Evolutionary Computing EvoWorkshops 2008: EvoCOMNET, EvoFIN, EvoHOT, EvoIASP, EvoMUSART, EvoNUM, EvoSTOC, and EvoTransLog, Naples, Italy, March 26-28, 2008. Berlin: Springer-Verlag, pp. 596-605.

Rights

Research Institute

Institute of Artificial Intelligence (IAI)